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06/30/2022
Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning
We introduce DeepNash, an autonomous agent capable of learning to play t...
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01/11/2021
Solving Common-Payoff Games with Approximate Policy Iteration
For artificially intelligent learning systems to have widespread applica...
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11/28/2020
Human-Agent Cooperation in Bridge Bidding
We introduce a human-compatible reinforcement-learning approach to a coo...
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04/20/2020
Approximate exploitability: Learning a best response in large games
A common metric in games of imperfect information is exploitability, i.e...
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11/19/2019
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
Constructing agents with planning capabilities has long been one of the ...
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08/26/2019
OpenSpiel: A Framework for Reinforcement Learning in Games
OpenSpiel is a collection of environments and algorithms for research in...
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03/13/2019
Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent
In this paper, we present exploitability descent, a new algorithm to com...
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07/05/2018
Consistent Generative Query Networks
Stochastic video prediction is usually framed as an extrapolation proble...
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06/05/2018
Relational Deep Reinforcement Learning
We introduce an approach for deep reinforcement learning (RL) that impro...
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02/23/2018
Efficient Neural Audio Synthesis
Sequential models achieve state-of-the-art results in audio, visual and ...
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11/28/2017